In many data communication applications, serializer and de-serializer (SerDes) devices facilitate the transmission of parallel data across a serial link. Parallel data is converted by the serializer at the transmitter to serial data before transmission through a communications channel to the receiver. A de-serializer in the receiver converts the serial data to parallel data. Signals arriving at the receiver are typically corrupted by intersymbol interference (ISI), crosstalk, echo and other noise. Thus, receivers typically amplify and equalize the channel to compensate for such distortions, often using a number of different equalization techniques. Decision-feedback equalization (DFE), for example, is a widely-used technique for removing intersymbol interference. For a detailed discussion of decision feedback equalizers, see, for example, R. Gitlin et al., Digital Communication Principles, (Plenum Press 1992) and E. A. Lee and D. G. Messerschmitt, Digital Communications, (Kluwer Academic Press, 1988), each incorporated by reference herein. Equalization may also be employed by the transmitter to pre-condition (e.g., pre-emphasize) the signal prior to transmission.
Equalization generally requires an estimate of the transfer function of the channel to establish the equalization parameters. The frequency-dependent signal degradation characteristics of the communications channel, however, often vary over time or may be not known a priori. Thus, in such environments, adaptive equalization is often employed to vary the equalization parameters over time to mitigate the signal degradation. In this manner, the equalization can adaptively respond to changes in channel characteristics or ambient conditions, such as temperature and humidity, and/or adapt from default values to the current channel characteristics. Adaptation algorithms typically adapt the filter coefficients in accordance with the signal statistics or the signal spectrum. For example, least mean square (LMS) adaptation techniques are often employed to establish the equalization parameters based on observations of the received signal over time.
Adaptation of the equalization parameters in the transmitter, however, may adversely impact the gain adjustments and/or equalization performed in the receiver (or vice versa). For example, in the case of high attenuation channels, it has been found that the equalizer coefficients in the transmitter are often increased towards their upper limits, causing the variable gain amplifier (VGA) in the receiver to likewise settle to its upper limits. Thus, the output of the VGA will not follow further increases in emphasis by the transmit equalizer. As a result, the data eye opening will be smaller and jitter tolerance in the receiver is reduced.
A need therefore exists for improved adaptive equalization techniques that adjust the transmitter equalization coefficients based on the gain adaptation in the receiver.